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Published on: February 16, 2024
Construction and validation of a prognostic model for children with acute upper gastrointestinal bleeding
Ruixue Li1, Yanmin Wu2, Wenting Zhang3
1Department of Pediatrics, Affiliated Hospital of Jiangnan University, Wuxi, China.
Insights
We developed a risk prediction model for pediatric acute upper gastrointestinal bleeding (AUGIB) using preoperative serum tests. This model effectively identifies children with a poor prognosis, aiding early intervention and reducing disease burden.
Area of Science:
- Pediatric Gastroenterology
- Biomarkers and Predictive Modeling
Background:
- Acute upper gastrointestinal bleeding (AUGIB) poses significant risks to children.
- Early identification of poor prognosis in pediatric AUGIB is crucial for reducing disease burden.
Purpose of the Study:
- To establish a risk prediction model for pediatric AUGIB prognosis.
- To provide a novel method for early identification of poor prognosis in children with AUGIB.
Main Methods:
- Binary logistic regression identified independent risk factors for AUGIB outcomes.
- A nomogram prediction model was constructed using neutrophil to leukocyte ratio (NLR), platelet to lymphocyte ratio (PLR), hemoglobin (Hb), high-sensitivity C-reactive protein (hsCRP), and activated partial thromboplastin time (APTT).
- Model performance was assessed using consistency index (C-index) and decision curve analysis (DCA).
Main Results:
- 372 children with AUGIB were included.
- NLR, PLR, Hb, hsCRP, and APTT were identified as independent risk factors.
- The nomogram model achieved a C-index of 0.945 (95% CI: 0.931-0.959), demonstrating strong predictive efficacy.
Conclusions:
- Preoperative serum tests offer an effective and objective method for predicting pediatric AUGIB prognosis.
- The developed prognostic risk prediction model accurately assesses the risk of poor outcomes in children with AUGIB, serving as a valuable clinical reference.
Background:
Gastrointestinal bleeding (GIB) is a common symptom of the pediatric digestive system, with acute upper gastrointestinal bleeding (AUGIB) being extremely dangerous for children. In the present study, we established a risk prediction model for the prognosis of children with AUGIB and provided a new method for early identification of poor prognosis, thereby reducing the disease burden.
Methods:
Binary logistic regression analysis was conducted to identify independent risk factors influencing the outcomes of children with AUGIB. The receiver operating characteristic curve (ROC) was generated to assess the predictive efficacy of these risk factors. A nomogram prediction model was constructed, and its performance was evaluated using the consistency index (C-index) and calibration curve. Decision curve analysis (DCA) was applied to estimate the clinical benefits of the intervention.
Results:
A total of 372 children who were diagnosed with AUGIB and met the inclusion criteria were enrolled in the study. Neutrophil to leukocyte ratio (NLR), platelet to lymphocyte ratio (PLR), hemoglobin (Hb), high-sensitivity C-reactive protein (hsCRP), and activated partial thromboplastin time (APTT) are independent influencing factors for the outcomes of AUGIB in children. The nomogram model was constructed by including the above independent influencing factors; the consistency index was 0.945 [95 confidence interval (CI): 0.931-0.959]. The DCA was used to assess the prediction performance of the model to obtain net clinical benefits.
Conclusion:
A preoperative serum test was an effective and objective method to predict the prognosis of children with AUGIB. The established prognostic risk prediction model had a good prediction effect; it could provide a reference to clinically assess the risk of poor prognosis in children with AUGIB.
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